SynthesisBJS open2020
Liquid biopsy for cancer diagnosis using vibrational spectroscopy: systematic review.
Synthesis in BJS open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Toward Informative Representations of Blood-Based Infrared Spectra via Unsupervised Deep Learning.Journal of biophotonics · 2025Article
- Bridging Spectral Gaps: Cross-Device Model Generalization in Blood-Based Infrared Spectroscopy.Analytical chemistry · 2025Article
- Synergistic strength: unleashing exercise and polyphenols against breast cancer.Cancer cell international · 2025Review
- Assessing lung cancer progression and survival with infrared spectroscopy of blood serum.BMC medicine · 2025Article
- Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening.Cell reports. Medicine · 2024Article
- Cervical Squamous Cell Carcinoma Diagnosis by FTIR Microspectroscopy.Molecules (Basel, Switzerland) · 2024Article
- Extracellular polymeric substances from marine actinobacterium ofJournal of advanced pharmaceutical technology & research · 2022Article
- Observational
- Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer.eLife · 2021Article
- Vibrational Spectroscopy: A Valuable Screening and Diagnostic Tool for Obstetric Disorders?Frontiers in global women's health · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVibrational spectroscopy (VS) is a minimally invasive tool for analysing biological material to detect disease. This study aimed to review its application to human blood for cancer diagnosis.
methodsA systematic review was undertaken using a keyword electronic database search (MEDLINE, Embase, PubMed, TRIP and Cochrane Library), with all original English-language manuscripts examining the use of vibrational spectral analysis of human blood for cancer detection. Studies involving fewer than 75 patients in the cancer or control group, animal studies, or where the primary analyte was not blood were excluded.
resultsFrom 1446 results, six studies (published in 2010-2018) examining brain, bladder, oral, breast, oesophageal and hepatic cancer met the criteria for inclusion, with a total population of 2392 (1316 cancer, 1076 control; 1476 men, 916 women). For cancer detection, reported mean sensitivities in each included study ranged from 79·3 to 98 per cent, with specificities of 82·8-95 per cent and accuracies between 81·1 and 97·1 per cent. Heterogeneity in reporting strategies, methods and outcome measures made meta-analysis inappropriate.
conclusionVS shows high potential for cancer diagnosis, but until there is agreement on uniform standard reporting methods and studies with adequate sample size for valid classification models have been performed, its value in clinical practice will remain uncertain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.